本文介绍了从Jupyter Notebook发布Azure ML Web服务的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
发布Azure ML Web服务时来自Jupyter笔记本,我们遇到了以下错误..
ValueErrorTraceback (most recent call last)
<ipython-input-4-7e2aa3c8d286> in <module>()
4 @services.publish('id','token')
5 @services.types(InvoiceNo=str,StockCode=str, Description=str,Quantity=float,UnitPrice=float,CustomerID=int,Country=str)
----> 6 @services.returns(str)
7
8
/home/nbuser/anaconda2_20/lib/python2.7/site-packages/azureml/services.pyc in do_publish(func)
939 if not callable(func_or_workspace_id):
940 def do_publish(func):
--> 941 func.service = _publish_worker(func, files, func_or_workspace_id, workspace_id_or_token, endpoint)
942 return func
943 return do_publish
/home/nbuser/anaconda2_20/lib/python2.7/site-packages/azureml/services.pyc in _publish_worker(func, files, workspace_id, workspace_token, management_endpoint)
883 msg = str(resp.status_code)
884 raise ValueError('Failed to publish function: ' + msg + chr(10) +
--> 885 'Set azureml.services._DEBUG = True to enable writing {}.req/{}.res files'.format(func.__name__, func.__name__))
886
887 j = resp.json()
ValueError: Failed to publish function: The request payload exceeds the maximum allowed request size of 134217728 bytes. Reduce the request payload size and try again.
Set azureml.services._DEBUG = True to enable writing customer_segmentor_Web.req/customer_segmentor_Web.res files
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